There is no doubt that with the acceleration of digital intelligence transformation, more and more companies are raising their digital intelligence strategy to a new level, and the process of transformation is also moving from "shallow level" digital intelligence to "deep level". Level" stage of digital intelligence.
According to statistics from authoritative organizations, the global digital economy has grown by 15.6% year-on-year in the past few years, and the number of companies adopting digital and intelligent transformation strategies has increased by 42% compared with two years ago. 16.5%. These data all show that more and more enterprises are accelerating digital intelligence transformation and increasing investment, hoping to use digital intelligence to face uncertainty, which also brings digital intelligence transformation into a new stage.
This has also brought the digital and intelligent transformation of enterprises into a new stage, and the challenges they are facing are getting bigger and bigger, including the fact that digital and intelligent transformation is bringing enterprises a wider range, more dimensions, and a higher level of internal and external At the same time, the technical complexity involved in transformation has also increased exponentially in the past few years, which also makes multi-technology collaboration more difficult.
At the same time, with the acceleration of business innovation, enterprise business scenarios are also facing diverse challenges, such as the Internetization of traditional business scenarios and the complexity of management and operations in new business scenarios. Therefore, how to integrate digital intelligence capabilities into business In production scenarios, it becomes more important to maximize the release of digital intelligence productivity. In addition, under the background of localization, how to build a safe and reliable digital intelligence base is also placed in front of many enterprises.
The digital and intelligent transformation is imminent, and how to quickly and efficiently carry out the digital and intelligent transformation of enterprises has become the most fundamental practical problem that needs to be solved urgently. The popular application of low-code development can well solve the digital and intelligent transformation problems faced by most enterprises.
Today, when low-code development is the general trend, many companies have personally felt the convenience brought by low-code development. The advantages of the low-code development platform provide enterprises with customized and exclusive digital solutions in the current wave of digitalization.
The JNPF rapid development platform has created a large number of "hard core achievements" for software services, manufacturing, education, government services and other fields, accumulated rich technical experience, and accumulated a large number of general solution templates for customer experience, which can quickly solve scenarios Pain points, to empower enterprises with digital intelligence.
JNPF deeply integrates java+.net 6 dual-technology engine, which has many characteristics such as easy maintenance, convenient deployment, high integration, and high efficiency. Life cycle capabilities. At the same time, it supports multiple cloud environment deployments, and local deployments provide maximum security, which can help enterprises quickly build products suitable for their own application scenarios.
There are two underlying logics of low-code, one is to improve the efficiency of enterprise application/system development and reduce the cost of digital transformation; the other is to promote everyone's development, so that business personnel can deeply participate in the construction of business systems, and finally realize business and digitalization Zero distance, that is, business digital native.
For professional large-scale system development: With the help of low-code development tools and AIGC development model, developers can improve the efficiency of each link from demand abstraction, business modeling, generation of functional modules, and subsequent testing and release; large-scale business The system is composed of many modules. Developers can focus on domain modeling, architecture design, solution design, code review, and integration of AI-generated module combinations with low-code; through AIGC capabilities, business personnel and developers can sort out various requirements documents , relatively simple and scattered application construction, partial function pages, deterministic function functions, etc., can all be assigned to AI generation.
For application development of small, medium and micro enterprises or department-level applications of large enterprises: business personnel can use low-code development tools and AIGC development mode to realize natural language description generation applications. The cross-input method generates simple applications.
On the contrary, building a unified enterprise digital platform based on a low-code platform can better control data security. Low-code has many aggregators of application flows that can make security efforts easier to manage across the enterprise. Low-code puts more emphasis on the ability of agile development, and based on this, it will be deeply integrated with digital technologies such as cloud computing, big data, Internet of Things, and blockchain, presenting a more automated and intelligent technology integration evolution form, allowing future The digital intelligence blueprint is more three-dimensional and diverse.